Three-dimensional visual phrases for object recognition
    1.
    发明授权
    Three-dimensional visual phrases for object recognition 有权
    用于对象识别的三维视觉短语

    公开(公告)号:US08983201B2

    公开(公告)日:2015-03-17

    申请号:US13561718

    申请日:2012-07-30

    IPC分类号: G06K9/46 G06K9/66

    CPC分类号: G06K9/46 G06K9/4676 G06K9/469

    摘要: The techniques discussed herein discover three-dimensional (3-D) visual phrases for an object based on a 3-D model of the object. The techniques then describe the 3-D visual phrases. Once described, the techniques use the 3-D visual phrases to detect the object in an image (e.g., object recognition).

    摘要翻译: 本文讨论的技术基于对象的3-D模型发现对象的三维(3-D)视觉短语。 然后,技术描述3-D视觉短语。 一旦描述,这些技术使用3-D视觉短语来检测图像中的对象(例如,对象识别)。

    THREE-DIMENSIONAL VISUAL PHRASES FOR OBJECT RECOGNITION
    2.
    发明申请
    THREE-DIMENSIONAL VISUAL PHRASES FOR OBJECT RECOGNITION 有权
    用于对象识别的三维视觉语法

    公开(公告)号:US20140029856A1

    公开(公告)日:2014-01-30

    申请号:US13561718

    申请日:2012-07-30

    IPC分类号: G06K9/46

    CPC分类号: G06K9/46 G06K9/4676 G06K9/469

    摘要: The techniques discussed herein discover three-dimensional (3-D) visual phrases for an object based on a 3-D model of the object. The techniques then describe the 3-D visual phrases. Once described, the techniques use the 3-D visual phrases to detect the object in an image (e.g., object recognition).

    摘要翻译: 本文讨论的技术基于对象的3-D模型发现对象的三维(3-D)视觉短语。 然后,技术描述3-D视觉短语。 一旦描述,这些技术使用3-D视觉短语来检测图像中的对象(例如,对象识别)。

    USER INTERFACE FOR THREE-DIMENSIONAL MODELING
    3.
    发明申请
    USER INTERFACE FOR THREE-DIMENSIONAL MODELING 有权
    用户界面进行三维建模

    公开(公告)号:US20140368620A1

    公开(公告)日:2014-12-18

    申请号:US13919933

    申请日:2013-06-17

    IPC分类号: H04N13/02 H04N5/232

    摘要: A method of acquiring a set of images useable to 3D model a physical object includes imaging the physical object with a camera, and displaying with the camera a current view of the physical object as imaged by the camera from a current perspective. The method further includes displaying with the camera a visual cue overlaying the current view and indicating perspectives from which the physical object is to be imaged to acquire the set of images.

    摘要翻译: 获取可用于对物理对象进行3D建模的一组图像的方法包括用相机对物理对象进行成像,并且从当前的角度通过相机显示物理对象的当前视图。 该方法还包括用相机显示覆盖当前视图的视觉提示,并且指示要从其中成像物理对象的视角以获取该组图像。

    Long-query retrieval
    4.
    发明授权
    Long-query retrieval 有权
    长查询检索

    公开(公告)号:US08326820B2

    公开(公告)日:2012-12-04

    申请号:US12571302

    申请日:2009-09-30

    IPC分类号: G06F17/30

    CPC分类号: G06F17/3028 G06F17/30448

    摘要: Described herein is a technology that facilitates efficient large-scale similarity-based retrieval. In several embodiments documents, images, and/or other multimedia files are compactly represented and efficiently indexed to enable robust search using a long-query in a large-scale corpus. As described herein, these techniques include performing decomposition of a file, e.g., a document or document-like representation. The techniques use dimension reduction to obtain three parts, topic-related words (major semantics), document specific words (minor semantics), and background words, representing the major semantics in a feature vector and the minor semantics as keywords. Using the techniques described, file vectors are matched in a topic model and the results ranked based on the keywords.

    摘要翻译: 这里描述了一种有助于有效的大规模相似性检索的技术。 在几个实施例中,文档,图像和/或其他多媒体文件被紧凑地表示并且被有效地索引,以使得能够使用大规模语料库中的长查询进行鲁棒搜索。 如这里所述,这些技术包括执行文件的分解,例如文档或类似文档的表示。 这些技术使用维度缩减来获得三个部分,主题相关词(主要语义),文档特定词(次要语义)和背景词,表示特征向量中的主要语义和次要语义作为关键字。 使用所描述的技术,在主题模型中匹配文件向量,并根据关键字对结果进行排名。

    Identifying visual contextual synonyms
    5.
    发明授权
    Identifying visual contextual synonyms 有权
    识别视觉上下文同义词

    公开(公告)号:US09082040B2

    公开(公告)日:2015-07-14

    申请号:US13107717

    申请日:2011-05-13

    IPC分类号: G06F17/30 G06K9/46

    摘要: Tools and techniques for identifying visual contextual synonyms are described herein. The described operations use visual words having similar contextual distributions as contextual synonyms to identify and describe visual objects that share semantic meaning. The contextual distribution of a visual word is described using the statistics of co-occurrence and spatial information averaged over image patches that share the visual word. In various implementations, the techniques are employed to construct a visual contextual synonym dictionary for a large visual vocabulary. In various implementations, the visual contextual synonym dictionary narrows the semantic gap for large-scale visual search.

    摘要翻译: 本文描述了用于识别视觉上下文同义词的工具和技术。 所描述的操作使用具有相似语境分布的视觉词作为上下文同义词来识别和描述共享语义意义的视觉对象。 使用共享视觉词的图像补丁上平均的同现和空间信息的统计来描述视觉词的语境分布。 在各种实现中,使用这些技术来构建用于大型视觉词汇表的视觉上下文同义词字典。 在各种实现中,视觉上下文同义词词典缩小了大规模视觉搜索的语义差距。

    IDENTIFYING VISUAL CONTEXTUAL SYNONYMS
    6.
    发明申请
    IDENTIFYING VISUAL CONTEXTUAL SYNONYMS 有权
    识别视觉语境同步

    公开(公告)号:US20120290577A1

    公开(公告)日:2012-11-15

    申请号:US13107717

    申请日:2011-05-13

    IPC分类号: G06F17/30

    摘要: Tools and techniques for identifying visual contextual synonyms are described herein. The described operations use visual words having similar contextual distributions as contextual synonyms to identify and describe visual objects that share semantic meaning. The contextual distribution of a visual word is described using the statistics of co-occurrence and spatial information averaged over image patches that share the visual word. In various implementations, the techniques are employed to construct a visual contextual synonym dictionary for a large visual vocabulary. In various implementations, the visual contextual synonym dictionary narrows the semantic gap for large-scale visual search.

    摘要翻译: 本文描述了用于识别视觉上下文同义词的工具和技术。 所描述的操作使用具有相似语境分布的视觉词作为上下文同义词来识别和描述共享语义意义的视觉对象。 使用共享视觉词的图像补丁上平均的同现和空间信息的统计来描述视觉词的语境分布。 在各种实现中,使用这些技术来构建用于大型视觉词汇表的视觉上下文同义词字典。 在各种实现中,视觉上下文同义词词典缩小了大规模视觉搜索的语义差距。

    Long-Query Retrieval
    7.
    发明申请
    Long-Query Retrieval 有权
    长查询检索

    公开(公告)号:US20110078159A1

    公开(公告)日:2011-03-31

    申请号:US12571302

    申请日:2009-09-30

    IPC分类号: G06F17/30

    CPC分类号: G06F17/3028 G06F17/30448

    摘要: Described herein is a technology that facilitates efficient large-scale similarity-based retrieval. In several embodiments documents, images, and/or other multimedia files are compactly represented and efficiently indexed to enable robust search using a long-query in a large-scale corpus. As described herein, these techniques include performing decomposition of a file, e.g., a document or document-like representation. The techniques use dimension reduction to obtain three parts, topic-related words (major semantics), document specific words (minor semantics), and background words, representing the major semantics in a feature vector and the minor semantics as keywords. Using the techniques described, file vectors are matched in a topic model and the results ranked based on the keywords.

    摘要翻译: 这里描述了一种有助于有效的大规模相似性检索的技术。 在几个实施例中,文档,图像和/或其他多媒体文件被紧凑地表示并且被有效地索引,以使得能够使用大规模语料库中的长查询进行鲁棒搜索。 如这里所述,这些技术包括执行文件的分解,例如文档或类似文档的表示。 这些技术使用维度缩减来获得三个部分,主题相关词(主要语义),文档特定词(次要语义)和背景词,表示特征向量中的主要语义和次要语义作为关键字。 使用所描述的技术,在主题模型中匹配文件向量,并根据关键字对结果进行排名。

    LEARNING TO RANK LOCAL INTEREST POINTS
    8.
    发明申请
    LEARNING TO RANK LOCAL INTEREST POINTS 审中-公开
    学习排名本地兴趣点

    公开(公告)号:US20120301014A1

    公开(公告)日:2012-11-29

    申请号:US13118282

    申请日:2011-05-27

    IPC分类号: G06K9/62 G06K9/46

    CPC分类号: G06K9/4676 G06F16/583

    摘要: Tools and techniques for learning to rank local interest points from images using a data-driven scale-invariant feature transform (SIFT) approach termed “Rank-SIFT” are described herein. Rank-SIFT provides a flexible framework to select stable local interest points using supervised learning. A Rank-SIFT application detects interest points, learns differential features, and implements ranking model training in the Gaussian scale space (GSS). In various implementations a stability score is calculated for ranking the local interest points by extracting features from the GSS and characterizing the local interest points based on the features being extracted from the GSS across images containing the same visual objects.

    摘要翻译: 本文描述了使用称为Rank-SIFT的数据驱动的尺度不变特征变换(SIFT)方法学习从图像对本地兴趣点进行排名的工具和技术。 Rank-SIFT提供了一个灵活的框架,使用监督学习选择稳定的本地兴趣点。 Rank-SIFT应用程序检测兴趣点,学习差异特征,并实现高斯尺度空间(GSS)中的排名模型训练。 在各种实施方式中,通过从GSS提取特征并基于从包含相同视觉对象的图像从GSS提取的特征来表征局部兴趣点来计算稳定性分数以对局部兴趣点进行排名。

    Image Search by Interactive Sketching and Tagging
    10.
    发明申请
    Image Search by Interactive Sketching and Tagging 有权
    图像搜索通过交互式草图和标记

    公开(公告)号:US20120072410A1

    公开(公告)日:2012-03-22

    申请号:US12883411

    申请日:2010-09-16

    IPC分类号: G06F17/30

    CPC分类号: G06F17/30268 G06F17/30277

    摘要: Sketch and tagging based image search may include receiving a sketch query input and identifying an object in a desired image. The object or objects of the sketch query may be tagged with a text, and searching performed based on the objects. Certain implementations include indexing patches of the images, where the patches represent the objects. Relevant images can be returned based on the index of the patches.

    摘要翻译: 基于草图和标记的图像搜索可以包括接收草图查询输入并识别所需图像中的对象。 草图查询的对象或对象可以被标记为文本,并且基于对象进行搜索。 某些实现包括索引图像的补丁,其中补丁代表对象。 可以根据补丁的索引返回相关图像。